knowledge-aware

SCHK-HTC is a novel method for few-shot hierarchical text classification that combines sibling contrastive learning with hierarchical knowledge-aware prompt tuning to better distinguish semantically similar classes at deeper hierarchy levels. The approach achieves state-of-the-art performance across three benchmark datasets by enhancing model perception of subtle differences between sibling classes.